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Hybrid Optimal Kinematic Parameter Identification for an Industrial Robot Based on BPNN-PSO

Author

Listed:
  • Guanbin Gao
  • Fei Liu
  • Hongjun San
  • Xing Wu
  • Wen Wang

Abstract

A novel hybrid algorithm that employs BP neural network (BPNN) and particle swarm optimization (PSO) algorithm is proposed for the kinematic parameter identification of industrial robots with an enhanced convergence response. The error model of the industrial robot is established based on a modified Denavit-Hartenberg method and Jacobian matrix. Then, the kinematic parameter identification of the industrial robot is transformed to a nonlinear optimization in which the unknown kinematic parameters are taken as optimal variables. A hybrid algorithm based on a BPNN and the PSO is applied to search for the optimal variables which are used to compensate for the error of the kinematic parameters and improve the positioning accuracy of the industrial robot. Simulations and experiments based on a realistic industrial robot are all provided to validate the efficacy of the proposed hybrid identification algorithm. The results show that the proposed parameter-identification method based on the BPNN and PSO has fewer iterations and faster convergence speed than the standard PSO algorithm.

Suggested Citation

  • Guanbin Gao & Fei Liu & Hongjun San & Xing Wu & Wen Wang, 2018. "Hybrid Optimal Kinematic Parameter Identification for an Industrial Robot Based on BPNN-PSO," Complexity, Hindawi, vol. 2018, pages 1-11, July.
    • Handle: RePEc:hin:complx:4258676
    DOI: 10.1155/2018/4258676
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    Cited by:

    1. Xin Xu & Ahmed Shaker & Marwa S. Salem, 2022. "Automatic Control of a Mobile Manipulator Robot Based on Type-2 Fuzzy Sliding Mode Technique," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    2. Sabir, Zulqurnain & Said, Salem Ben & Baleanu, Dumitru, 2022. "Swarming optimization to analyze the fractional derivatives and perturbation factors for the novel singular model," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    3. Zhihong Wu & Ruifeng Yang & Chenxia Guo & Shuangchao Ge & Xiaole Chen, 2019. "Analysis and Verification of Finite Time Servo System Control with PSO Identification for Electric Servo System," Energies, MDPI, vol. 12(18), pages 1-19, September.

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